Senior Machine Learning Engineer

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We are looking for a Senior Machine Learning Engineer to lead complex ML and big data projects at our new Data Center and Networking AI Team to solve some of the hardest and most interesting technological challenges facing the industry today.

About the Team:

You will be joining a new team of world-class high-performing and low ego engineers and scientists that have an entrepreneurial and hacker spirit. The team will operate in a very self-driven, agile and fast-paced environment. The team operates by self-organizing, around shared values, vision and objectives.


  • 5-7 years of experience as a software engineer building and shipping production quality code in C/C++, Java, Python, or similar language
  • Minimum of 2 years of experience working on big data problems (in terabytes) using technologies like Cassandra, Hadoop, and Spark
  • Experience working on data modeling, data pipelines, and building warehouses projects
  • Experience deploying machine learning models to production is a MUST
  • Experience building container-based applications running in a microservice architecture on Kubernetes or serverless
  • Comfortable researching and reading research papers and implementing models
  • Comfortable experimenting with and incorporating cutting-edge techniques into our existing system, such as online learning, transfer learning, and few-shot learning
  • Deep understanding of model training, what affects performance (hyperparameters, data distribution, etc)
  • Ability to write an end-to-end pipeline code that is modular, scalable, and easy for future team members to build upon


  • Master’s Degree in computer science or engineering

Additional Qualifications:

  • Experience working on time interval problems
  • Experience with data analysis and visualization
  • Extract meaningful insights from the data and present to leadership

Rakuten Americas at a glance

Rakuten Americas focuses on E-Commerce, Curated Web, Canada, and United States. Their company has offices in San Francisco Bay Area and San Mateo. They have a very large team that's 5000+ employees.

You can view their website at or find them on Twitter, Facebook, and LinkedIn.

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